Chapter 18 Data Analysis Overview Yandell – Econ 216 Chap 18-1.

Slides:



Advertisements
Similar presentations
CHAPTER TWELVE ANALYSING DATA I: QUANTITATIVE DATA ANALYSIS.
Advertisements

PSY 307 – Statistics for the Behavioral Sciences Chapter 20 – Tests for Ranked Data, Choosing Statistical Tests.
Chapter 10 Two-Sample Tests
QUANTITATIVE DATA ANALYSIS
Chapter 13 Conducting & Reading Research Baumgartner et al Data Analysis.
Basic Statistical Review
Chapter 13 Analyzing Quantitative data. LEVELS OF MEASUREMENT Nominal Measurement Ordinal Measurement Interval Measurement Ratio Measurement.
Final Review Session.
Chapter 19 Data Analysis Overview
Data Analysis Statistics. Inferential statistics.
Review What you have learned in QA 128 Business Statistics I.
Educational Research by John W. Creswell. Copyright © 2002 by Pearson Education. All rights reserved. Slide 1 Chapter 8 Analyzing and Interpreting Quantitative.
Copyright ©2011 Pearson Education, Inc. publishing as Prentice Hall 18-1 Chapter 18 Data Analysis Overview Statistics for Managers using Microsoft Excel.
Summary of Quantitative Analysis Neuman and Robson Ch. 11
Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc. Chap 10-1 Chapter 10 Two-Sample Tests Basic Business Statistics 10 th Edition.
Statistical Analysis KSE966/986 Seminar Uichin Lee Oct. 19, 2012.
© 2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
© 2005 The McGraw-Hill Companies, Inc., All Rights Reserved. Chapter 12 Describing Data.
Fall 2013 Lecture 5: Chapter 5 Statistical Analysis of Data …yes the “S” word.
Census A survey to collect data on the entire population.   Data The facts and figures collected, analyzed, and summarized for presentation and.
ITEC6310 Research Methods in Information Technology Instructor: Prof. Z. Yang Course Website: c6310.htm Office:
Choosing and using statistics to test ecological hypotheses
Statistics & Biology Shelly’s Super Happy Fun Times February 7, 2012 Will Herrick.
Chapter 9 Hypothesis Testing and Estimation for Two Population Parameters.
Chapter 15 Data Analysis: Testing for Significant Differences.
A Repertoire of Hypothesis Tests  z-test – for use with normal distributions and large samples.  t-test – for use with small samples and when the pop.
Research Methods in Human-Computer Interaction
RESULTS & DATA ANALYSIS. Descriptive Statistics  Descriptive (describe)  Frequencies  Percents  Measures of Central Tendency mean median mode.
Lecture 5: Chapter 5: Part I: pg Statistical Analysis of Data …yes the “S” word.
PCB 3043L - General Ecology Data Analysis. OUTLINE Organizing an ecological study Basic sampling terminology Statistical analysis of data –Why use statistics?
11 Chapter 12 Quantitative Data Analysis: Hypothesis Testing © 2009 John Wiley & Sons Ltd.
Recap of data analysis and procedures Food Security Indicators Training Bangkok January 2009.
Determination of Sample Size: A Review of Statistical Theory
Lesson 15 - R Chapter 15 Review. Objectives Summarize the chapter Define the vocabulary used Complete all objectives Successfully answer any of the review.
STATISTICAL ANALYSIS FOR THE MATHEMATICALLY-CHALLENGED Associate Professor Phua Kai Lit School of Medicine & Health Sciences Monash University (Sunway.
© Copyright McGraw-Hill Correlation and Regression CHAPTER 10.
Academic Research Academic Research Dr Kishor Bhanushali M
Descriptive & Inferential Statistics Adopted from ;Merryellen Towey Schulz, Ph.D. College of Saint Mary EDU 496.
Review Lecture 51 Tue, Dec 13, Chapter 1 Sections 1.1 – 1.4. Sections 1.1 – 1.4. Be familiar with the language and principles of hypothesis testing.
Introduction to Basic Statistical Tools for Research OCED 5443 Interpreting Research in OCED Dr. Ausburn OCED 5443 Interpreting Research in OCED Dr. Ausburn.
Chapter Eight: Using Statistics to Answer Questions.
Chap 18-1 Copyright ©2012 Pearson Education, Inc. publishing as Prentice Hall Chap 18-1 Chapter 18 A Roadmap for Analyzing Data Basic Business Statistics.
STATISTICS AND OPTIMIZATION Dr. Asawer A. Alwasiti.
Mr. Magdi Morsi Statistician Department of Research and Studies, MOH
The field of statistics deals with the collection,
PCB 3043L - General Ecology Data Analysis.
Copyright © 2011, 2005, 1998, 1993 by Mosby, Inc., an affiliate of Elsevier Inc. Chapter 19: Statistical Analysis for Experimental-Type Research.
Lesson 14 - R Chapter 14 Review. Objectives Summarize the chapter Define the vocabulary used Complete all objectives Successfully answer any of the review.
1 UNIT 13: DATA ANALYSIS. 2 A. Editing, Coding and Computer Entry Editing in field i.e after completion of each interview/questionnaire. Editing again.
LIS 570 Summarising and presenting data - Univariate analysis.
Statistics with TI-Nspire™ Technology Module E Lesson 1: Elementary concepts.
Educational Research: Data analysis and interpretation – 1 Descriptive statistics EDU 8603 Educational Research Richard M. Jacobs, OSA, Ph.D.
MATHS CORE AND OPTIONAL ASSESSMENT STANDARDS Found in the Subject Assessment Guidelines (SAG) Dated January 2008.
Statistics & Evidence-Based Practice
Chapter 12 Understanding Research Results: Description and Correlation
Chapter 14 Introduction to Multiple Regression
Statistics in Management
Review 1. Describing variables.
PCB 3043L - General Ecology Data Analysis.
Module 6: Descriptive Statistics
Georgi Iskrov, MBA, MPH, PhD Department of Social Medicine
Stats Club Marnie Brennan
Introduction to Statistics
Basic Statistical Terms
15.1 The Role of Statistics in the Research Process
Review for Exam 1 Ch 1-5 Ch 1-3 Descriptive Statistics
Chapter Nine: Using Statistics to Answer Questions
Georgi Iskrov, MBA, MPH, PhD Department of Social Medicine
Introductory Statistics
Examine Relationships
Presentation transcript:

Chapter 18 Data Analysis Overview Yandell – Econ 216 Chap 18-1

Learning Objectives In this chapter, you learn: The steps involved in choosing what statistical methods to use to conduct a data analysis Yandell – Econ 216 Chap 18-2

Good Data Analysis Requires Choosing The Proper Technique(s) Choosing the proper technique(s) to use requires the consideration of: The purpose of the analysis The type of variable being analyzed Numerical Categorical The assumptions about the variable you are willing to make Yandell – Econ 216 Chap 18-3

Questions To Ask When Analyzing Numerical Variables Do you seek to: Describe the characteristics of the variable (possibly broken into several groups) Draw conclusions about the mean and standard deviation of the variable in a population Determine whether the mean and standard deviation of the variable differs depending on the group Determine which factors affect the value of the variable Predict the value of the variable based on the value of other variables Determine whether the values of the variable are stable over time Yandell – Econ 216 Chap 18-4

How to Describe the Characteristics of a Numerical Variable Develop tables and charts and compute descriptive statistics to describe the variable’s characteristics: Tables and charts Stem-and-leaf display, percentage distribution, histogram, polygon, boxplot, normal probability plot Statistics Mean, median, mode, quartiles, range, interquartile range, standard deviation, variance, and coefficient of variation Yandell – Econ 216 Chap 18-5

How to draw conclusions about the population mean or standard deviation Confidence interval for the mean based on the t-distribution Hypothesis test for the mean (t-test) Yandell – Econ 216 Chap 18-6

How to determine whether the mean or standard deviation differs by group Two independent groups studying central tendency Normally distributed numerical variables Pooled t-test if you can assume variances are equal Separate-variance t-test if you cannot assume variances are equal Both tests assume the variables are normally distributed and you can examine this assumption by developing boxplots and normal probability plots To decide if the variances are equal you can conduct an F- test for the ratio of two variances Numerical variables not normally distributed Wilcoxon rank sum test Yandell – Econ 216 Chap 18-7

How to determine whether the mean or standard deviation differs by group Two groups of matched items or repeated measures studying central tendency Paired differences normally distributed Paired t-test Two independent groups studying variability Numerical variables normally distributed F-test continued Yandell – Econ 216 Chap 18-8

Three or more independent groups and studying central tendency Numerical variables normally distributed One Way Analysis of Variance Numerical variables not normally distributed Kruskal-Wallis Rank Test continued Yandell – Econ 216 Chap 18-9 How to determine whether the mean or standard deviation differs by group

How to determine which factors affect the value of the variable Two factors to be examined Two-factor factorial design Yandell – Econ 216 Chap 18-10

How to predict the value of a variable based on the value of other variables One independent variable Simple linear regression model Two or more independent variables Multiple regression model Data taken over a period of time and you want to forecast future time periods Moving averages Exponential smoothing Least-squares forecasting Autoregressive modeling Yandell – Econ 216 Chap 18-11

How to determine whether the values of a variable are stable over time Studying a process and have collected data over time Develop R and charts Yandell – Econ

Questions To Ask When Analyzing Categorical Variables Do you seek to: Describe the proportion of items of interest in each category (possibly broken into several groups) Draw conclusions about the proportion of items of interest in a population Determine whether the proportion of items of interest differs depending on the group Predict the proportion of items of interest based on the value of other variables Determine whether the proportion of items of interest is stable over time Yandell – Econ 216 Chap 18-13

How to describe the proportion of items of interest in each category Summary tables Charts Bar chart Pie chart Pareto chart Side-by-side bar charts Yandell – Econ 216 Chap 18-14

How to draw conclusions about the proportion of items of interest Confidence interval for proportion of items of interest Hypothesis test for the proportion of items of interest (Z-test) Yandell – Econ 216 Chap 18-15

How to determine whether the proportion of items of interest differs depending on the group Categorical variable has two categories Two independent groups Two proportion Z-test for the difference between two proportions Two groups of matched or repeated measurements McNemar test More than two independent groups for the difference among several proportions More than two categories and more than two groups of independence    test Yandell – Econ 216 Chap 18-16

How to determine whether the proportion of items of interest is stable over time Studying a process and data is taken over time Collected items of interest over time p-chart Yandell – Econ 216 Chap 18-17

Data Analysis Tree Numerical & Categorical Variables Numerical Variables Categorical Variables Possible Questions How to describe the characteristics of the variable (possibly broken into several groups)? How to draw conclusions about the mean and standard deviation of the variable in the population? How to determine whether the mean and standard deviation of the variable differs depending on the group? How to determine which factors affect the value of the variable? How to predict the value of the variable based on the value of other variables? How to determine whether the values of the variable are stable over time? How to describe the proportion of items of interest in each category (possibly broken into several groups)? How to draw conclusions about the proportion of items of interest in a population? How to determine whether the proportion of items of interest differs depending on the group? How to predict the proportion of items of interest based on the value of other variables? How to determine whether the proportion of items of interest is stable over time? Yandell – Econ 216 Chap 18-18

Data Analysis Tree Numerical Variables How to describe the characteristics of the variable (possibly broken into several groups)? How to draw conclusions about the mean and standard deviation of the variable in the population? How to determine whether the mean and standard deviation of the variable differs depending on the group? continued Create Tables & Charts Calculate Statistics Mean Variance Stem-and-leaf display, percentage distribution, histogram, polygon, boxplot, normal probability plot Mean, median, mode, quartiles, range, interquartile range, standard deviation, variance, coefficient of variation Confidence interval for mean (t or z) Hypothesis test for mean (t or z) Pooled t test (both variables must be normal, variances equal) Separate variance t test ( both variables must be normal) Wilcoxon rank sum test ( variables do not have to be normal) F-test ( both variables must be normal) Paired t test (differences must be normal) One Way Anova (variable must be normal) Kruskal-Wallis Rank Test (variable doesn’t need to be normal) 2 independent groups 2 matched groups >2 independent groups Yandell – Econ 216 Chap 18-19

Data Analysis Tree Numerical Variables continued How to determine which factors affect the value of the variable? How to predict the value of the variable based on the value of other variables? How to determine whether the values of the variable are stable over time? Two factors to be examined One independent variable Two or more Independent variables Data taken over time to forecast the future Studied a process and taken data over time Two factor factorial design Simple linear regression Multiple regression model Moving averages Exponential smoothing Least squares forecasting Autoregressive modeling Develop and R charts Yandell – Econ 216 Chap 18-20

Data Analysis Tree Categorical Variables continued How to describe the proportion of items of interest in each category (possibly broken into several groups) How to draw conclusions about the proportion of items of interest in a population How to determine whether the proportion of items of interest differs depending on the group Summary tables Bar charts Pie charts Pareto charts Side-by-side charts Confidence interval for the proportion of items of interest Hypothesis test for the proportion of items of interest Two proportion Z test test for the difference between two proportions McNemar test test for the difference among several proportions test of independence Two categories & two independent groups Two categories & two matched groups Two categories & more than two independent groups More than two categories & more than two groups Yandell – Econ 216 Chap 18-21

How to determine whether the proportion of items of interest is stable over time continued p-chart Studying a process and collected items of interest over time Yandell – Econ 216 Chap Data Analysis Tree Categorical Variables

Chapter Summary Discussed how to choose the appropriate technique(s) for data analysis for both numerical and categorical variables Discussed potential questions and the associated appropriate techniques for numerical variables Discussed potential questions and the associated appropriate techniques for categorical variables Yandell – Econ 216 Chap 18-23